Load service metadata, plans, and recent artifacts into a conversation.
npx skills add https://github.com/cfarvidson/sapling --skill context-cfarvidson
Please help me install this Agent Skill. Skill: context Source: https://github.com/cfarvidson/sapling/tree/main/packages/claude-plugin/skills/context Command: npx skills add https://github.com/cfarvidson/sapling --skill context-cfarvidson
This Skill resolves the issue of agents not having access to the necessary context when working on a service, ensuring they can ground themselves and perform their tasks effectively.
To load the context for a service, use the command: /sapling:context <service>
High-intent search queries and answers about installing and using this skill.
You can load service metadata, plans, and recent artifacts into your conversation by invoking the /sapling:context <service> command. This populates the context with service name, repository, tech stack, dependencies, and conventions for agent grounding.
Before working on a service, an agent needs contextual information including service metadata, repository details, tech stack, dependencies, conventions, and lists of recent plans and artifacts with their IDs and statuses.
No, you cannot use this context loading approach without access. The skill explicitly requires access to service information and the ability to list plans and recent artifacts to successfully load the complete service context.
The best way to provide service understanding is to load complete context directly into the conversation. This gives the agent a comprehensive overview of the project scope, ensuring it can ground itself and make informed decisions.
No external dependencies are required to list recent artifacts. The skill operates independently using its internal scripts and references to retrieve service metadata, plans, and artifact details.
Your agent lacks project scope understanding because it does not have access to necessary service context. Loading detailed metadata, plans, and recent artifacts resolves this issue by grounding the agent before task execution.
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